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Comparing the performance of Random Forests and Logistic Regression on a binary classification problem to predict whether a medical patient’s breast tumor is malignant or benign

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craigmacartney/Comparison-of-Random-Forests-and-Logistic-Regression-on-Wisconsin-Breast-Cancer-Dataset--Diagnostic

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Comparison-of-Random-Forests-and-Logistic-Regression-on-Wisconsin-Breast-Cancer-Dataset-Diagnostic-

Comparing the performance of Random Forests and Logistic Regression on a binary classification problem to predict whether a medical patient’s breast tumor is malignant or benign

Breast Cancer Wisconsin (Diagnostic) Data Set - Lichman, M. (2013). UCI Machine Learning Repository [https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29]. Irvine, CA: University of California, School of Information and Computer Science.

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Comparing the performance of Random Forests and Logistic Regression on a binary classification problem to predict whether a medical patient’s breast tumor is malignant or benign

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